sklearn 机器学习模型应用

1、生产训练及测试集

from sklearn.model_selection import train_test_split
x_train, x_test, y_train, y_test = train_test_split(data_train, data_target)
print(x_test.shape)

2、SVM

from sklearn import svm
model = svm.SVC()  # 建模
model.fit(x_train, y_train)  # 训练
score = model.score(x_test, y_test)  # 评分
print(score)

3.K临近回归器

from sklearn.neighbors import KNeighborsRegressor
knn = KNeighborsRegressor(weights="uniform")
knn.fit(x_train, y_train)
score = knn.score(x_test, y_test)
print(score)